Guiding the Training of Users With a Pattern Similarity Biofeedback to Improve the Performance of Myoelectric Pattern Recognition (bibtex)
by , , , , ,
Bibtex Entry:
@Article{2020ACLI4834,
  author   = {de Montalivet, E and Bailly, K and Touillet, A and Martinet, N and Paysant, J and Jarrassé, N},
  title    = {Guiding the Training of Users With a Pattern Similarity Biofeedback to Improve the Performance of Myoelectric Pattern Recognition},
  journal  = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
  year     = {2020},
  volume   = {28},
  number   = {8},
  pages    = {1731 - 1741},
  abstract = {Most transhumeral amputated individuals deplore the lack of functionality of their prosthesis due to control-related limitations. Commercialized prosthetic elbows are controlled via myoelectric signals, yielding complex control schemes when users have to control an entire prosthetic limb. Limited control yields the development of compensatory strategies. An alternative control strategy associates residual limb motions to automatize the prosthetic elbow motion using a model of physiological shoulder/elbow synergies. Preliminary studies have shown that elbow motion could be predicted from residual limb kinematic measurements, but results with transhumeral amputated individuals were lacking. This study focuses on the experimental assessment of automatic prosthetic elbow control during a reaching task, compared to conventional myoelectric control, with six transhumeral amputated individuals, among whom, three had an osseointegrated device. Part of the recruited participants had an osseointegrated prosthetic device. The task was achieved within physiological precision errors with both control modes. Automatic elbow control reduced trunk compensations, and restored a physiologically-like shoulder/elbow movement synchronization. However, the kinematic assessment showed that amputation and prosthesis wear modifies the shoulder movements in comparison with physiological shoulder kinematics. Overall, participants described the automatic elbow control strategy as intuitive, and this work highlights the interest of automatized prosthetic elbow motion.},
  category = {ACLI},
  crac     = {n},
  doi      = {10.1109/TNSRE.2020.3003077},
  file     = {:http\://www.isir.upmc.fr/files/2020ACLI4834.pdf:PDF;:http\://www.n-jarrasse.fr/publis_medias/2020ACLI4834.jpg:JPG image},
  hal      = {y},
}
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